Summary translation

Legumes as protein feedstuffs could solve the problems of protein supply in organic farming, but the variations in chemical composition and especially in contents of essential amino acids lead to handling problems for the farmer. Therefore it is necessary to determine the most important ingredients fast and easy directly after harvesting. The analytical potential of Near-Infrared Spectroscopy (NIRS) should be used for predicting the chemical composition of grain legumes. The basic for a successful application of the NIRS are stable calibration equations for the prediction of the ingredients. NIR-spectra combined with chemometric algorithms and reference analyses were used to develop accurate and stable calibrations. The legumes peas and beans should be included in the project. Samples from mixed cropping field trials from two years conducted at different stations in Germany and the experimental station of the Institute of Organic Farming in Trenthorst were used for the investigations, in total 450 samples. The legumes were analysed by classical chemical methods and also by NIRS. The main ingredients of the legumes were determined according to VDLUFA methods, the contents of amino acid by HPLC. NIRS analysis was carried out on the ground samples using a Fourier-Transform NIR spectrometer in the spectral range from 1000 to 2500 nm. Spectral data were submitted different mathematical pretreatments. Calibration equations were calculated by partial least square regression on about two-thirds of the samples. The calibration equations were than validated on the remaining one-third of the samples. Calibration equations were evaluated in terms of standard error of calibration and coefficient of determination, validation equations were evaluated in terms of standard error of prediction and coefficient of determination. The obtained results from the first growing season, especially the prediction accuracy should be improved with samples from a second growing season.